Mitfed: A privacy preserving collaborative network attack mitigation framework based on federated learning using sdn and blockchain
Distributed denial-of-service (DDoS) attacks continue to grow at a rapid rate plaguing
Internet Service Providers (ISPs) and individuals in a stealthy way. Thus, intrusion detection …
Internet Service Providers (ISPs) and individuals in a stealthy way. Thus, intrusion detection …
An end-to-end framework for machine learning-based network intrusion detection system
The increase of connected devices and the constantly evolving methods and techniques by
attackers pose a challenge for network intrusion detection systems from conception to …
attackers pose a challenge for network intrusion detection systems from conception to …
Intelligent intrusion detection for internet of things security: A deep convolutional generative adversarial network-enabled approach
With the rapid advance of Internet of Things (IoT), it is difficult for cloud-centric computing to
meet the requirements of low latency and ease of use. As an open and distributed system …
meet the requirements of low latency and ease of use. As an open and distributed system …
G-VCFL: Grouped verifiable chained privacy-preserving federated learning
Federated learning, as a typical distributed learning paradigm, shows great potential in
Industrial Internet of Things, Smart Home, Smart City, etc. It enables collaborative learning …
Industrial Internet of Things, Smart Home, Smart City, etc. It enables collaborative learning …
A machine learning model for detection of docker-based APP overbooking on kubernetes
Resource allocation overbooking is an approach used by cloud providers that allocates
more virtual resources than available on physical hardware, which may imply service quality …
more virtual resources than available on physical hardware, which may imply service quality …
Deep learning-based network intrusion detection in smart healthcare enterprise systems
V Ravi - Multimedia Tools and Applications, 2024 - Springer
Network-based intrusion detection (N-IDS) is an essential system inside an organization in a
smart healthcare enterprise system to prevent the system and its networks from network …
smart healthcare enterprise system to prevent the system and its networks from network …
A deep one-class intrusion detection scheme in software-defined industrial networks
B Hu, Y Bi, M Zhi, K Zhang, F Yan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The unprecedented development of intelligent manufacturing requires to customize and
change the network traffic strategies frequently. With the advantages of highagility and …
change the network traffic strategies frequently. With the advantages of highagility and …
Intrusion detection method based on smote transformation for smart grid cybersecurity
Real-time Intrusion Detection Systems (IDSs) have attracted greater attention for secured
and resilient smart grid operations. IDSs are employed to identify unknown cyberattacks and …
and resilient smart grid operations. IDSs are employed to identify unknown cyberattacks and …
Towards multi-view android malware detection through image-based deep learning
Over the last years, several works have proposed highly accurate Android malware
detection techniques. Surprisingly, modern malware apps can still pave their way to official …
detection techniques. Surprisingly, modern malware apps can still pave their way to official …
Improving the accuracy of network intrusion detection with causal machine learning
Z Zeng, W Peng, B Zhao - Security and Communication …, 2021 - Wiley Online Library
In recent years, machine learning (ML) algorithms have been approved effective in the
intrusion detection. However, as the ML algorithms are mainly applied to evaluate the …
intrusion detection. However, as the ML algorithms are mainly applied to evaluate the …